Patient Experience Journal (Aug 2021)

Sociodemographic characteristics and patient and family experience survey response biases

  • Lauren Brinkman,
  • Myra Saeed,
  • Andrew Beck,
  • Michael Ponti-Zins,
  • Ndidi Unaka,
  • Mary Burkhardt,
  • Jareen Meinzen-Derr,
  • Samuel Hanke

Abstract

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Enhancing Patient and Family Experience (PFE) is vital to the delivery of quality healthcare services. Sociodemographic differences affect health outcomes and experiences, but research is limited on biases in PFE survey methodology. We sought to assess survey participation rates across sociodemographic characteristics. This retrospective study analyzed a health system’s ambulatory PFE survey data, collected January 1 – July 31, 2019. Outcomes of interest were rates of survey response, completion, and comments. Predictors included respondent-reported race, ethnicity, language, and measure of social deprivation attached to a respondent’s home address. Addresses were geocoded to census tracts. The tract’s degree of socioeconomic deprivation was defined using the Deprivation Index (DPI). Associations between outcomes and predictors were assessed using the Chi square test. 77,627 unique patient encounters were analyzed. Patients were predominantly White (76%); 5% were Hispanic; and 1% were Spanish-speaking. The overall response, completion, and comment rates were 20.1%, 17.6%, and 4.1%, respectively. There were significant differences across assessed sociodemographic characteristics in response, completion, and comment rates. White patients were most likely to respond, complete, and leave a comment. Spanish-speaking respondents and those living in the most deprived areas were more likely to respond and complete the survey, but less likely to comment than English-speaking respondents and those living in less deprived areas, respectively. PFE survey participation differs across a range of sociodemographic characteristics, potentially introducing noteworthy biases. Health systems should minimize differences in how they collect feedback and account for potential biases when responding to experience data. Experience Framework This article is associated with the Policy & Measurement lens of The Beryl Institute Experience Framework. (https://www.theberylinstitute.org/ExperienceFramework). Access other PXJ articles related to this lens. Access other resources related to this lens.

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